AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
python
nlp
svm
scikit-learn
sklearn
regression
logistic
dnn
lstm
pca
rnn
deeplearning
kmeans
adaboost
apriori
fp-growth
svd
naivebayes
mahchine-leaning
recommendedsystem
-
Updated
Jun 1, 2020 - Python
In Python XGBoost one can provide weights for each row of the data, see http://xgboost.readthedocs.io/en/latest/python/python_api.html#xgboost.XGBClassifier.fit. I tried to look for a way to specify such weights in SharpLearning, but could not find it. Is this possible?